CN112465966A  Cliff threedimensional modeling method integrating oblique photogrammetry and threedimensional laser scanning  Google Patents
Cliff threedimensional modeling method integrating oblique photogrammetry and threedimensional laser scanning Download PDFInfo
 Publication number
 CN112465966A CN112465966A CN202011311379.XA CN202011311379A CN112465966A CN 112465966 A CN112465966 A CN 112465966A CN 202011311379 A CN202011311379 A CN 202011311379A CN 112465966 A CN112465966 A CN 112465966A
 Authority
 CN
 China
 Prior art keywords
 dimensional
 data
 point cloud
 dimensional laser
 laser scanning
 Prior art date
 Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
 Pending
Links
 238000000034 method Methods 0.000 title claims abstract description 37
 238000005259 measurement Methods 0.000 claims abstract description 9
 230000004927 fusion Effects 0.000 claims description 23
 238000006243 chemical reaction Methods 0.000 claims description 11
 238000012545 processing Methods 0.000 claims description 9
 239000011159 matrix material Substances 0.000 claims description 6
 238000013519 translation Methods 0.000 claims description 6
 230000003247 decreasing effect Effects 0.000 claims description 4
 238000007499 fusion processing Methods 0.000 claims description 4
 238000004364 calculation method Methods 0.000 claims description 3
 238000000354 decomposition reaction Methods 0.000 claims description 3
 238000007781 preprocessing Methods 0.000 claims description 3
 238000005070 sampling Methods 0.000 claims description 3
 230000009466 transformation Effects 0.000 claims description 3
 238000000844 transformation Methods 0.000 claims description 3
 238000005034 decoration Methods 0.000 claims description 2
 230000000694 effects Effects 0.000 abstract description 4
 230000007547 defect Effects 0.000 abstract description 2
 238000012544 monitoring process Methods 0.000 abstract description 2
 238000012937 correction Methods 0.000 description 2
 238000012800 visualization Methods 0.000 description 2
 230000009286 beneficial effect Effects 0.000 description 1
 238000010586 diagram Methods 0.000 description 1
 239000004579 marble Substances 0.000 description 1
 238000011160 research Methods 0.000 description 1
 239000004575 stone Substances 0.000 description 1
Images
Classifications

 G—PHYSICS
 G06—COMPUTING; CALCULATING OR COUNTING
 G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
 G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
 G06T17/05—Geographic models

 G—PHYSICS
 G01—MEASURING; TESTING
 G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
 G01B11/00—Measuring arrangements characterised by the use of optical techniques
 G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates

 G—PHYSICS
 G01—MEASURING; TESTING
 G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
 G01B11/00—Measuring arrangements characterised by the use of optical techniques
 G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures

 G—PHYSICS
 G01—MEASURING; TESTING
 G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
 G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
 G01C11/04—Interpretation of pictures
 G01C11/06—Interpretation of pictures by comparison of two or more pictures of the same area
 G01C11/08—Interpretation of pictures by comparison of two or more pictures of the same area the pictures not being supported in the same relative position as when they were taken

 G—PHYSICS
 G06—COMPUTING; CALCULATING OR COUNTING
 G06F—ELECTRIC DIGITAL DATA PROCESSING
 G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
 G06F17/10—Complex mathematical operations
 G06F17/16—Matrix or vector computation, e.g. matrixmatrix or matrixvector multiplication, matrix factorization

 G—PHYSICS
 G06—COMPUTING; CALCULATING OR COUNTING
 G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
 G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
 G06T17/20—Finite element generation, e.g. wireframe surface description, tesselation

 G—PHYSICS
 G06—COMPUTING; CALCULATING OR COUNTING
 G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
 G06T7/00—Image analysis
 G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
 G06T7/33—Determination of transform parameters for the alignment of images, i.e. image registration using featurebased methods
 G06T7/344—Determination of transform parameters for the alignment of images, i.e. image registration using featurebased methods involving models

 G—PHYSICS
 G06—COMPUTING; CALCULATING OR COUNTING
 G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
 G06T2207/00—Indexing scheme for image analysis or image enhancement
 G06T2207/10—Image acquisition modality
 G06T2207/10028—Range image; Depth image; 3D point clouds
Landscapes
 Engineering & Computer Science (AREA)
 Physics & Mathematics (AREA)
 General Physics & Mathematics (AREA)
 Theoretical Computer Science (AREA)
 Software Systems (AREA)
 Geometry (AREA)
 Mathematical Physics (AREA)
 Data Mining & Analysis (AREA)
 Mathematical Optimization (AREA)
 Remote Sensing (AREA)
 Pure & Applied Mathematics (AREA)
 Computational Mathematics (AREA)
 Computer Graphics (AREA)
 Mathematical Analysis (AREA)
 Computing Systems (AREA)
 Multimedia (AREA)
 Computer Vision & Pattern Recognition (AREA)
 Algebra (AREA)
 Radar, Positioning & Navigation (AREA)
 Databases & Information Systems (AREA)
 General Engineering & Computer Science (AREA)
 Image Analysis (AREA)
 Image Processing (AREA)
 Length Measuring Devices By Optical Means (AREA)
Abstract
The invention discloses a threedimensional modeling method for a cliff, which integrates oblique photogrammetry and threedimensional laser scanning; the threedimensional laser scanning technology is fused with point cloud data acquired by unmanned aerial vehicle lowaltitude oblique photogrammetry, and the method can be applied to the fields of archaeology, ancient building modeling, deformation monitoring and the like; the method of combining the ground and the air is adopted for collection, and the defects of measurement model drawing, bottom effect, scanning blind areas shielded from each other in the front and back direction and the like can be mutually compensated by the ground and the air.
Description
Technical Field
The invention belongs to the technical field of geological measurement, and particularly relates to a threedimensional cliff modeling method integrating oblique photogrammetry and threedimensional laser scanning.
Background
Due to the self shape, a plurality of data source acquisition blind points exist in the process of establishing a threedimensional model of a special geographic structure, such as occlusion, angle and position limitation, and if a single device is adopted to acquire a single data source, complete threedimensional point cloud data is difficult to acquire; the geological landform threedimensional model established only through a single data source has certain limitations on quality and precision; therefore, the threedimensional modeling by using multiple devices, multiple platforms and multiangle data source acquisition and fusion is an effective way for solving the problems and is also a current research hotspot; the multiplatform data acquisition can exert respective advantages, different acquisition modes can adapt to different structural data acquisition, and finally fusion processing is carried out through the data sources acquired in multiple modes, so that the limitation of acquiring the data sources in a single mode can be broken;
the threedimensional laser scanning technology is fused with point cloud data acquired by unmanned aerial vehicle lowaltitude oblique photogrammetry, and the method can be applied to the fields of archaeology, ancient building modeling, deformation monitoring and the like; the method of combining the ground and the air is adopted for collection, and the defects of measurement model drawing, bottom effect, scanning blind areas shielded from each other in the front and back direction and the like can be mutually compensated by the ground and the air.
Disclosure of Invention
The invention aims to solve the problems that the acquisition of a single data source by single equipment is difficult to obtain complete threedimensional point cloud data, and a threedimensional model established by the single data source has certain limitations on quality and precision;
in order to solve the technical problems, the invention is realized by the following technical scheme: a cliff threedimensional modeling method integrating oblique photogrammetry and threedimensional laser scanning mainly comprises the following four steps: acquiring data of a ground type threedimensional laser scanning technology, acquiring data of an unmanned aerial vehicle oblique photogrammetry technology, fusing multipoint cloud data and establishing a threedimensional model;
further, the groundbased threedimensional laser scanning technology data acquisition comprises the following steps:
(1) performing site survey to determine a main scanning area, and then performing approximate determination of a scanning survey station for the scanning area;
(2) laying a control network, performing control measurement, and obtaining a control point coordinate as a reference for calculating coordinates of the measuring station;
(3) placing a threedimensional laser scanner, setting parameters of the instrument, and then collecting data;
(4) preprocessing point cloud data by using scanner matching software Maptek ISite Studio, such as splicing, denoising and the like;
furthermore, in the step (3), the stations are increased or decreased according to the actual situation during data acquisition, generally, on the premise of ensuring the precision, a few viewpoints are used for covering the measurement area, and a sketch is drawn during scanning to facilitate the internal data processing;
furthermore, when the measuring stations are added, the position information of the measuring stations can be unknown, but a scanning area has a certain overlapping degree which is generally not less than 30%; the target can also be used, the target is placed in the scanning area, adjacent stations have at least 3 public targets which are not on the same straight line, and if 4 targets are arranged, the targets are not on the same plane; measuring the accurate coordinates of the target so as to provide a registration reference for the scanning data of different stations;
further, the unmanned aerial vehicle oblique photogrammetry technology data acquisition comprises the following steps:
(1) before data acquisition, control and image control point layout are carried out on a measuring area;
(2) carrying out route planning and adjustment setting of corresponding parameters on the survey area; course overlap 80%, side overlap 80%, flight path high distance departure point height 150 meters;
(3) controlling a 4Pro UAV (unmanned aerial vehicle) for acquiring data;
(4) during data processing, the fuzzy photos are removed, and CntextCapture Center software is adopted for processing to generate point cloud data;
further, the multipoint cloud data fusion adopts a method of combining a unified coordinate system method and an improved ICP algorithm, and the specific steps are as follows:
p is respectively used for threedimensional laser point cloud and unmanned aerial vehicle oblique photogrammetry image conversion point cloud_{T}，P_{S}Indicating, deleting P_{S}In the method, redundant data which does not need to be fused are processed by a unified coordinate method at P_{T}，P_{S}And searching for the samename point pair for rough fusion. The data volume of multipoint cloud is large, and P is added for improving the fusion efficiency_{T}，P_{S}Is uniformly sampled to obtainAnd finding out local features in the multipoint cloud fusion interface part, and performing rapid fusion on the local features by using an improved ICP algorithm.
And (3) adding a human rotation angle constraint and a dynamic generation coefficient to improve the ICP algorithm:
(1) given the initial q of rigid body transformation_{0}＝[R_{0},t_{0}]^{T}，R_{0}Is an initial rotation matrix, t_{0}As an initial translation vector, letThe iteration number k is 0, and the dynamic iteration coefficient h is 0;
(2) estimating a rotation angle θ_{x}，θ_{y}，θ_{z}Is a boundary of, i.e. theta_{x}∈[θ_{xb}Δθ_{x},θ_{xb}+Δθ_{x}]，θ_{y}∈[θ_{yb}Δθ_{y},θ_{yb}+Δθ_{y}]，θ_{z}∈[θ_{zb}Δθ_{z},θ_{zb}+Δθ_{z}]，θ_{xb}，θ_{yb}，θ_{zb}Is the mean of the rotation angles;
(4) Calculation of rotation matrix R by singular value decomposition_{k+1}And a translation vector t_{k+1}Q is then_{k+1}＝[R_{k+1},t_{k+1}]^{T}；
(5) Calculating q_{k+1}Of two adjacent iterations Δ q_{k+1}；
(7) Determining the root mean square error RMS, if RSM_{k+1}RSM_{k}If > epsilon, then hh +1 operation is performed, otherwise h0 operation is performed, and RMS is defined as
(8) Judging the dynamic generation coefficient h, if h is greater than 0, executingUpdating point set h times
(9) Determining the termination condition, if the termination condition satisfies the  RMS_{k+1}RMS_{k}< ε  or k > Step_{max}The algorithm terminates, otherwise moves to Step (10), ε is a preset threshold, Step_{max}Is the maximum number of generations;
(10) let k be k +1 and go to step (2).
Further, the threedimensional model is established in a mode of reconstructing fused multipoint clouds according to a Delaunay space triangulation algorithm or in a mode of respectively reconstructing unmanned aerial vehicle oblique photogrammetry image conversion point clouds and threedimensional laser scanning point clouds, and then models obtained in the two modes are fused into a complete threedimensional model;
further, the fused multipoint cloud is reconstructed according to a Delaunay space triangulation algorithm, and before multipoint cloud data fusion, the point cloud data of the unmanned aerial vehicle oblique photogrammetry image conversion is removed or the data with unsatisfactory quality is removed, and the threedimensional laser point cloud data is filtered in a unified sampling mode; in the data fusion process, data fusion is not needed to be carried out on all the areas, and only the part with data missing is fused.
The invention has the beneficial effects that: the oblique photogrammetry technology is combined with the ground threedimensional laser scanning technology to be applied to the high cliff, and the unmanned aerial vehicle oblique photogrammetry image conversion point cloud data and the ground laser scanning point cloud data are subjected to registration and fusion, so that ground threedimensional laser scanning dead angles are supplemented, and the integrity of the point cloud data of the high cliff is ensured. Because threedimensional laser penetrability is good, data accuracy is high, can be applied to unmanned aerial vehicle oblique photogrammetry's measured data correction or repair the threedimensional model with threedimensional laser scanning technique, solve the not good and local flower problem of data quality. The threedimensional model built by fusing data has good integrity, strong authenticity, scalability and undistorted proportion, and can obtain better visualization effect and engineering practicability.
Drawings
Fig. 1 is a block diagram of the steps of a threedimensional modeling method for a cliff integrating oblique photogrammetry and threedimensional laser scanning.
Detailed Description
The present invention will be further described with reference to the following specific examples, but the scope of the present invention is not limited to the contents of the examples;
example 1
The embodiment is based on a Yunnan marble customs scenic spot, is positioned in the Xipo Yangbi county of the cangshan, is a geological park of the cangshan, is located at the west foot of the Longshan Longquan peak and Yujufeng and is located at the east bank of Yangjiang; the scarp is Vshaped, the inclination angle of two walls is about 90 degrees, the scarp is about 450 meters high and is more than one thousand meters long, two quay walls of the canyon are broken by a thousand of the scarp, and a huge stone is abrupt;
1. the method comprises the following steps of performing data acquisition of a ground type threedimensional laser scanning technology:
(1) performing site survey to determine a main scanning area, and then performing approximate determination of a scanning survey station for the scanning area;
(2) laying a control network, performing control measurement, and obtaining a control point coordinate as a reference for calculating coordinates of the measuring station;
(3) placing a threedimensional laser scanner, setting parameters of the instrument, and then collecting data; the measurement stations are increased or decreased according to actual conditions during data acquisition, a measurement area is covered by fewer viewpoints on the premise of ensuring the precision, and a sketch is drawn during scanning so as to facilitate the processing of internal data;
(4) preprocessing point cloud data by using scanner matching software Maptek ISite Studio, such as splicing, denoising and the like;
according to the actual situation of a field, the position information of the measuring station can be unknown when the measuring station needs to be added, but a scanning area has a certain overlapping degree which is generally not less than 30%; the target can also be used, the target is placed in the scanning area, adjacent stations have at least 3 public targets which are not on the same straight line, and if 4 targets are arranged, the targets are not on the same plane; and measuring the accurate coordinates of the target so as to provide a registration reference for the scanning data of different stations.
2. The method comprises the following steps of carrying out data acquisition of the unmanned aerial vehicle oblique photogrammetry technology:
(1) before data acquisition, control and image control point layout are carried out on a measuring area;
(2) carrying out route planning and adjustment setting of corresponding parameters on the survey area; course overlap 80%, side overlap 80%, flight path high distance departure point height 150 meters;
(3) controlling a 4Pro UAV (unmanned aerial vehicle) for acquiring data;
(4) during data processing, the fuzzy photos are removed, and CntextCapture Center software is adopted for processing to generate point cloud data;
3. the method for fusing multipoint cloud data by combining a unified coordinate system method and an improved ICP algorithm comprises the following specific steps:
p is respectively used for threedimensional laser point cloud and unmanned aerial vehicle oblique photogrammetry image conversion point cloud_{T}，P_{S}Indicating, deleting P_{S}In the method, redundant data which does not need to be fused are processed by a unified coordinate method at P_{T}，P_{S}And searching for the samename point pair for rough fusion. The data volume of multipoint cloud is large, and P is added for improving the fusion efficiency_{T}，P_{S}Is uniformly sampled to obtainAnd finding out local features in the multipoint cloud fusion interface part, and performing rapid fusion on the local features by using an improved ICP algorithm.
And (3) adding a human rotation angle constraint and a dynamic generation coefficient to improve the ICP algorithm:
(8) given the initial q of rigid body transformation_{0}＝[R_{0},t_{0}]^{T}，R_{0}Is an initial rotation matrix, t_{0}As an initial translation vector, letThe iteration number k is 0, and the dynamic iteration coefficient h is 0;
(9) estimating a rotation angle θ_{x}，θ_{y}，θ_{z}Is a boundary of, i.e. theta_{x}∈[θ_{xb}Δθ_{x},θ_{xb}+Δθ_{x}]，θ_{y}∈[θ_{yb}Δθ_{y},θ_{yb}+Δθ_{y}]，θ_{z}∈[θ_{zb}Δθ_{z},θ_{zb}+Δθ_{z}]，θ_{xb}，θ_{yb}，θ_{zb}Is the mean of the rotation angles;
(11) Calculation of rotation matrix R by singular value decomposition_{k+1}And a translation vector t_{k+1}Q is then_{k+1}＝[R_{k+1},t_{k+1}]^{T}；
(12) Calculating q_{k+1}Of two adjacent iterations Δ q_{k+1}；
(14) Determining the root mean square error RMS, if RSM_{k+1}RSM_{k}If > epsilon, then hh +1 operation is performed, otherwise h0 operation is performed, and RMS is defined as
(8) Judging the dynamic generation coefficient h, if h is greater than 0, executingUpdating point set h times
(9) Determining the termination condition, if the termination condition satisfies the  RMS_{k+1}RMS_{k}< ε  or k > Step_{max}The algorithm terminates, otherwise moves to Step (10), ε is a preset threshold, Step_{max}Is the maximum number of generations;
(10) let k be k +1 and go to step (2).
4. Establishing a threedimensional modeling mode by adopting a mode of reconstructing fused multipoint cloud according to a Delaunay space triangulation algorithm or a mode of respectively reconstructing a threedimensional model by unmanned aerial vehicle oblique photogrammetry image conversion point cloud and a threedimensional laser scanning point cloud, and then fusing the models obtained in the two modes into a complete threedimensional model; two modes can be selected from one mode to perform threedimensional modeling;
the fused multipoint cloud is reconstructed in a Delaunay space triangulation algorithm mode, and before multipoint cloud data fusion, point cloud decoration or data with unsatisfactory quality of unmanned aerial vehicle oblique photogrammetry image conversion are respectively eliminated, and threedimensional laser point cloud data are filtered in a unified sampling mode; in the data fusion process, data fusion is not needed to be carried out on all the areas, and only the part with data missing is fused.
In summary, the oblique photogrammetry technology is combined with the ground threedimensional laser scanning technology to be applied to the high cliff, and the unmanned aerial vehicle oblique photogrammetry image conversion point cloud data and the ground laser scanning point cloud data are registered and fused, so that the ground threedimensional laser scanning dead angle is supplemented, and the integrity of the point cloud data of the high cliff is ensured. Because threedimensional laser penetrability is good, data accuracy is high, can be applied to unmanned aerial vehicle oblique photogrammetry's measured data correction or repair the threedimensional model with threedimensional laser scanning technique, solve the not good and local flower problem of data quality. The threedimensional model built by fusing data has good integrity, strong authenticity, scalability and undistorted proportion, and can obtain better visualization effect and engineering practicability.
Claims (8)
1. A cliff threedimensional modeling method integrating oblique photogrammetry and threedimensional laser scanning mainly comprises the following three steps: the method comprises the steps of ground type threedimensional laser scanning technology data acquisition, unmanned aerial vehicle oblique photogrammetry technology data acquisition, multipoint cloud data fusion and threedimensional model establishment.
2. The cliff threedimensional modeling method integrating oblique photogrammetry and threedimensional laser scanning as recited in claim 1, wherein the groundbased threedimensional laser scanning technology data acquisition comprises the following steps:
(1) performing site survey to determine a main scanning area, and then performing approximate determination of a scanning survey station for the scanning area;
(2) laying a control network, performing control measurement, and obtaining a control point coordinate as a reference for calculating coordinates of the measuring station;
(3) placing a threedimensional laser scanner, setting parameters of the instrument, and then collecting data;
(4) and (3) carrying out preprocessing such as splicing, denoising and the like on the point cloud data by using scanner matching software Maptek ISite Studio.
3. The threedimensional modeling method for the cliff integrating oblique photogrammetry and threedimensional laser scanning as claimed in claim 2, wherein in the step (3), stations are increased or decreased according to actual conditions during data acquisition, generally, on the premise of ensuring accuracy, a measuring area is covered by fewer viewpoints, and a sketch is drawn during scanning to facilitate internal data processing.
4. The threedimensional modeling method for the cliff integrating oblique photogrammetry and threedimensional laser scanning as claimed in claim 3, wherein the stations are increased or decreased according to actual conditions during data acquisition, and when the stations are increased, the position information of the stations can be unknown, but the scanning area has a certain overlapping degree, generally not less than 30%; the target can also be used, the target is placed in the scanning area, adjacent stations have at least 3 public targets which are not on the same straight line, and if 4 targets are arranged, the targets are not on the same plane; and measuring the accurate coordinates of the target so as to provide a registration reference for the scanning data of different stations.
5. The threedimensional cliff modeling method integrating oblique photogrammetry and threedimensional laser scanning as recited in claim 1, wherein the unmanned aerial vehicle oblique photogrammetry technology data acquisition comprises the following steps:
(1) before data acquisition, control and image control point layout are carried out on a measuring area;
(2) carrying out route planning and adjustment setting of corresponding parameters on the survey area; course overlap 80%, side overlap 80%, flight path high distance departure point height 150 meters;
(3) controlling a 4Pro UAV (unmanned aerial vehicle) for acquiring data;
(4) and during data processing, the fuzzy photos are removed, and CntextCapture Center software is adopted for processing to generate point cloud data.
6. The cliff threedimensional modeling method integrating oblique photogrammetry and threedimensional laser scanning as claimed in claim 1, wherein the multipoint cloud data fusion adopts a method combining a unified coordinate system method and an improved ICP algorithm, and comprises the following specific steps:
p is respectively used for threedimensional laser point cloud and unmanned aerial vehicle oblique photogrammetry image conversion point cloud_{T}，P_{S}Indicating, deleting P_{S}In the method, redundant data which does not need to be fused are processed by a unified coordinate method at P_{T}，P_{S}And searching for the samename point pair for rough fusion. The data volume of multipoint cloud is large, and P is added for improving the fusion efficiency_{T}，P_{S}Is uniformly sampled to obtainAnd finding out local features in the multipoint cloud fusion interface part, and performing rapid fusion on the local features by using an improved ICP algorithm.
And (3) adding a human rotation angle constraint and a dynamic generation coefficient to improve the ICP algorithm:
(1) given the initial q of rigid body transformation_{0}＝[R_{0},t_{0}]^{T}，R_{0}Is an initial rotation matrix, t_{0}As an initial translation vector, letThe iteration number k is 0, and the dynamic iteration coefficient h is 0;
(2) estimating a rotation angle θ_{x}，θ_{y}，θ_{z}Is a boundary of, i.e. theta_{x}∈[θ_{xb}Δθ_{x},θ_{xb}+Δθ_{x}]，θ_{z}∈[θ_{zb}Δθ_{z},θ_{zb}+Δθ_{z}]，θ_{xb}，θ_{yb}，θ_{zb}Is the mean of the rotation angles;
(4) Calculation of rotation matrix R by singular value decomposition_{k+1}And a translation vector t_{k+1}Q is then_{k+1}＝[R_{k+1},t_{k+1}]^{T}；
(5) Calculating q_{k+1}Of two adjacent iterations Δ q_{k+1}；
(7) Determining the root mean square error RMS, if RSM_{k+1}RSM_{k}If > epsilon, then hh +1 operation is performed, otherwise h0 operation is performed, and RMS is defined as
(8) Judging the dynamic generation coefficient h, if h is greater than 0, executingUpdating points h timesCollection
(9) Determining the termination condition, if the termination condition satisfies the  RMS_{k+1}RMS_{k}< ε  or k > Step_{max}The algorithm terminates, otherwise moves to Step (10), ε is a preset threshold, Step_{max}Is the maximum number of generations;
(10) let k be k +1 and go to step (2).
7. The threedimensional cliff modeling method integrating oblique photogrammetry and threedimensional laser scanning as claimed in claim 1, wherein the threedimensional model is built in a mode of reconstructing a fused multipoint cloud according to a Delaunay space triangulation algorithm or in a mode of respectively reconstructing a threedimensional model by using an unmanned aerial vehicle oblique photogrammetry image conversion point cloud and a threedimensional laser scanning point cloud, and then the models obtained in the two modes are fused into a complete threedimensional model.
8. The threedimensional cliff modeling method integrating oblique photogrammetry and threedimensional laser scanning as claimed in claim 7, wherein the fused multipoint cloud is reconstructed by a Delaunay space triangulation algorithm, and before multipoint cloud data fusion, unmanned aerial vehicle oblique photogrammetry image conversion point cloud decoration or data with poor quality are respectively removed and threedimensional laser point cloud data are filtered by a uniform sampling method; in the data fusion process, data fusion is not needed to be carried out on all the areas, and only the part with data missing is fused.
Priority Applications (1)
Application Number  Priority Date  Filing Date  Title 

CN202011311379.XA CN112465966A (en)  20201120  20201120  Cliff threedimensional modeling method integrating oblique photogrammetry and threedimensional laser scanning 
Applications Claiming Priority (1)
Application Number  Priority Date  Filing Date  Title 

CN202011311379.XA CN112465966A (en)  20201120  20201120  Cliff threedimensional modeling method integrating oblique photogrammetry and threedimensional laser scanning 
Publications (1)
Publication Number  Publication Date 

CN112465966A true CN112465966A (en)  20210309 
Family
ID=74799303
Family Applications (1)
Application Number  Title  Priority Date  Filing Date 

CN202011311379.XA Pending CN112465966A (en)  20201120  20201120  Cliff threedimensional modeling method integrating oblique photogrammetry and threedimensional laser scanning 
Country Status (1)
Country  Link 

CN (1)  CN112465966A (en) 
Cited By (4)
Publication number  Priority date  Publication date  Assignee  Title 

CN113393507A (en) *  20210630  20210914  南京工业大学  Unmanned aerial vehicle point cloud and ground threedimensional laser scanner point cloud registration method 
CN114623804A (en) *  20220311  20220614  浙江泰乐地理信息技术股份有限公司  Oblique photography measurement method and measurement system based on multipoint laser assistance 
CN115018971A (en) *  20220130  20220906  青岛市勘察测绘研究院  Spatial grid model construction method 
CN115307611A (en) *  20220712  20221108  宁夏超高压电力工程有限公司  Substation unmanned aerial vehicle oblique photography modeling and autonomous inspection method 
Citations (3)
Publication number  Priority date  Publication date  Assignee  Title 

CN105931234A (en) *  20160419  20160907  东北林业大学  Ground threedimensional laser scanning point cloud and image fusion and registration method 
CN109978791A (en) *  20190328  20190705  苏州市建设工程质量检测中心有限公司  A kind of bridge monitoring methods merged based on oblique photograph and 3 D laser scanning 
CN110276732A (en) *  20190618  20190924  昆明理工大学  A kind of mountain area point cloud cavity restorative procedure for taking features of terrain line feature into account 

2020
 20201120 CN CN202011311379.XA patent/CN112465966A/en active Pending
Patent Citations (3)
Publication number  Priority date  Publication date  Assignee  Title 

CN105931234A (en) *  20160419  20160907  东北林业大学  Ground threedimensional laser scanning point cloud and image fusion and registration method 
CN109978791A (en) *  20190328  20190705  苏州市建设工程质量检测中心有限公司  A kind of bridge monitoring methods merged based on oblique photograph and 3 D laser scanning 
CN110276732A (en) *  20190618  20190924  昆明理工大学  A kind of mountain area point cloud cavity restorative procedure for taking features of terrain line feature into account 
NonPatent Citations (2)
Title 

佘智渊: "基于三维激光扫描的校园建筑三维建模", 《甘肃科技》 * 
冯鸣等: "三维激光扫描与倾斜摄影测量的高陡崖三维建模", 《测绘科学》 * 
Cited By (6)
Publication number  Priority date  Publication date  Assignee  Title 

CN113393507A (en) *  20210630  20210914  南京工业大学  Unmanned aerial vehicle point cloud and ground threedimensional laser scanner point cloud registration method 
CN113393507B (en) *  20210630  20230728  南京工业大学  Unmanned aerial vehicle point cloud and ground threedimensional laser scanner point cloud registration method 
CN115018971A (en) *  20220130  20220906  青岛市勘察测绘研究院  Spatial grid model construction method 
CN114623804A (en) *  20220311  20220614  浙江泰乐地理信息技术股份有限公司  Oblique photography measurement method and measurement system based on multipoint laser assistance 
CN114623804B (en) *  20220311  20240611  浙江泰乐地理信息技术股份有限公司  Oblique photogrammetry method and measurement system based on multipoint laser assistance 
CN115307611A (en) *  20220712  20221108  宁夏超高压电力工程有限公司  Substation unmanned aerial vehicle oblique photography modeling and autonomous inspection method 
Similar Documents
Publication  Publication Date  Title 

CN110503080B (en)  Investigation method based on unmanned aerial vehicle oblique photography auxiliary sewage draining exit  
CN112465966A (en)  Cliff threedimensional modeling method integrating oblique photogrammetry and threedimensional laser scanning  
CN111322994B (en)  Largescale cadastral survey method for intensive house area based on unmanned aerial vehicle oblique photography  
CN102506824B (en)  Method for generating digital orthophoto map (DOM) by urban low altitude unmanned aerial vehicle  
CN111597666B (en)  Method for applying BIM to transformer substation construction process  
CN113192193B (en)  Highvoltage transmission line corridor threedimensional reconstruction method based on Cesium threedimensional earth frame  
CN109685886A (en)  A kind of distribution threedimensional scenic modeling method based on mixed reality technology  
CN112762899B (en)  Fusion method of laser point cloud and BIM model with video information in visual transformer substation  
CN106846308A (en)  The detection method and device of the topographic map precision based on a cloud  
CN111091076B (en)  Tunnel limit data measuring method based on stereoscopic vision  
Renaudin et al.  Featured‐Based Registration of Terrestrial Laser Scans with Minimum Overlap Using Photogrammetric Data  
Jebur et al.  Assessing the performance of commercial Agisoft PhotoScan software to deliver reliable data for accurate3D modelling  
WO2022104251A1 (en)  Image analysis for aerial images  
CN111006645A (en)  Unmanned aerial vehicle surveying and mapping method based on motion and structure reconstruction  
CN113763570B (en)  Highprecision rapid automatic splicing method for point cloud of tunnel  
Rebelo et al.  Building 3D city models: Testing and comparing Laser scanning and lowcost UAV data using FOSS technologies  
CN113345084A (en)  Threedimensional modeling system and threedimensional modeling method  
He et al.  Construction of 3D Model of Tunnel Based on 3D Laser and Tilt Photography.  
CN116385692A (en)  Ground threedimensional laser scanner site optimization arrangement method for bridge detection scene  
CN112815911B (en)  Transmission line crossing distance measuring method based on trinocular vision  
CN112505723B (en)  Threedimensional map reconstruction method based on navigation point selection  
Gu et al.  Surveying and mapping of largescale 3D digital topographic map based on oblique photography technology  
Chen et al.  3D model construction and accuracy analysis based on UAV tilt photogrammetry  
Yu et al.  Application of terrestrial 3d laser scanning technology in spatial information acquisition of urban buildings  
Huang et al.  An Innovative Approach of Evaluating the Accuracy of Point Cloud Generated by PhotogrammetryBased 3D Reconstruction 
Legal Events
Date  Code  Title  Description 

PB01  Publication  
PB01  Publication  
SE01  Entry into force of request for substantive examination  
SE01  Entry into force of request for substantive examination  
RJ01  Rejection of invention patent application after publication 
Application publication date: 20210309 

RJ01  Rejection of invention patent application after publication 